Designing of Polymers for Photovoltaics Applications and Prediction of Band Gap as a Polymers Screening Criterion
Nafees Ahmad, Ihab Mohamed Moussa, Asif Mahmood, Yingping Zou
Abstract
The development of efficient and sustainable energy sources has propelled research into organic photovoltaics (OPVs), where polymers play a critical role as active materials. Designing polymers for photovoltaic applications involves optimizing their molecular structure to achieve desirable electronic properties, such as a suitable band gap, which directly influences the efficiency of solar energy conversion. In this study, we present a systematic approach for the design and screening of polymers for OPV applications, focusing on the prediction and tuning of band gaps as a key criterion. Six machine learning models are tried. Random Forest is selected as the best model; it shows an r-squared value of 0.78 and root mean squared error value of 0.7 eV. A library of 20,000 polymers is curated and analyzed. Polymers are screened on the basis of predicted band gap values, and 30 polymers are selected. Selected polymers have a band gap between 1.18 and 1.97 eV. Chemical similarity analysis has indicated similar structural behavior for selected polymers.